Robust Principal Component Analysis For Computing The Degradation Rates Of Different Photovoltaic Systems. Kyprianou, A.; Phinikarides, A.; Makrides, G.; and Georghiou, G. E In 29th EU-PVSEC, pages 2939–2942.
doi  abstract   bibtex   
A new methodology for computing degradation rates of photovoltaic (PV) systems based on robust principal component analysis (PCA) is proposed. Conventional PCA demonstrates that performance ratio (PR), Rp, time series contain two significant features attributed to seasonality and uncertainty. Robust PCA is used in order to remove the effects of uncertainty from the original PR time series. The data obtained after removing the effects of uncertainty is then used for computing a newly defined degradation rate measure, which is based on the area enclosed by the curves of the PR time series of the first and the last year of evaluation. In addition, the degradation rate results are compared with those obtained in the previous studies using the conventional linear regression methodology.
@inproceedings{kyprianouRobustPrincipalComponent2014,
  location = {{Amsterdam}},
  title = {Robust {{Principal Component Analysis For Computing The Degradation Rates Of Different Photovoltaic Systems}}},
  doi = {10.4229/EUPVSEC20142014-5BV.2.41},
  abstract = {A new methodology for computing degradation rates of photovoltaic (PV) systems based on robust principal component analysis (PCA) is proposed. Conventional PCA demonstrates that performance ratio (PR), Rp, time series contain two significant features attributed to seasonality and uncertainty. Robust PCA is used in order to remove the effects of uncertainty from the original PR time series. The data obtained after removing the effects of uncertainty is then used for computing a newly defined degradation rate measure, which is based on the area enclosed by the curves of the PR time series of the first and the last year of evaluation. In addition, the degradation rate results are compared with those obtained in the previous studies using the conventional linear regression methodology.},
  booktitle = {29th {{EU}}-{{PVSEC}}},
  date = {2014},
  pages = {2939--2942},
  keywords = {degradation,pv modules,experimental methods,award},
  author = {Kyprianou, Andreas and Phinikarides, Alexander and Makrides, George and Georghiou, George E},
  file = {/home/alexis/Zotero/storage/2PHI4DXN/Robust Principal Component Analysis For Computing The Degradation Rates Of - 2014.pdf}
}
Downloads: 0